Gartner Report
Modern Data and Analytics Requirements Demand a Convergence of Data Management Capabilities
As modern data and analytics solutions evolves, so do data management capabilities
Growing modern data and analytics investments demand new data management solutions to meet changing business requirements and new analytics use cases. The point solutions of yesterday are no longer sufficient, and we believe Gartner is seeing some convergence of capabilities in the market—data leaders should take note. Two examples of this convergence include data integration with data catalog tools, as well as data integration with data quality tools.
- IT and the business need a more integrated approach to handle data quality, data definitions and metadata management, as well as search and governance.
- Many data management functions, from data profiling to integration, are appearing in applications and tools that blur lines in the traditional landscape.
- Data leaders should look into solutions with aggregated metadata management capabilities that can span the organization's many analytics use cases.
Data leaders need a new approach to data management with an integrated solution
With the right solution that minimizes the number of tools for the broadest use cases, data management and metadata management can help IT and the business to better communicate and collaborate on innovate, digital initiatives.
Read the Gartner report to get a better understanding of the changing landscape, including valuable survey data and statistics cited in additional Gartner research, including:
- Gartner's 2019 CEO Survey: The Year of Challenged Growth
- Gartner's Fourth Annual CDO Survey
- Gartner's Hype Cycle for Data Management 2019
- Gartner's The State of Metadata Management
You'll also get recommendations from Gartner around understanding critical data management capabilities, including how to think about them holistically in the context of your organization's needs. This means not only looking at the state of data management in your organization today, but considering immediate and future needs as analytics use cases grow and business requirements evolve.